Modeling Binary Lenses and Sources with the BAGLE Python Package
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866910076439101440 |
|---|---|
| author | Bhadra, T. Dex Lu, J. R. Abrams, Natasha S. Scharf, Andrew Broadberry, Edward Lam, Casey Huston, Macy J. |
| author_facet | Bhadra, T. Dex Lu, J. R. Abrams, Natasha S. Scharf, Andrew Broadberry, Edward Lam, Casey Huston, Macy J. |
| contents | Gravitational microlensing is a powerful tool that can be used to find and measure the mass of isolated and dark compact objects. In many microlensing events, the lens, the source, or both may be a binary system. In this work, we introduce binary source and lens models into the gravitational lensing formalism encoded in the Bayesian Analysis of Gravitational Lensing Events (BAGLE) Python software package. These new binary models in BAGLE account for Keplerian orbits. We also add binary models with fewer parameters that describe the binary orbital motion as acceleration, linear, or stationary motion of the secondary companion; these are useful when the orbit has a very low eccentricity or the orbital period is much longer than the microlensing timescale. The model parameterizations based on these binary lensing equations enable joint-fitting of photometric and astrometric datasets. These binary models will be used to fit microlensing event data from the Vera C. Rubin Observatory, the Nancy Grace Roman Telescope, and other surveys. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_03392 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Modeling Binary Lenses and Sources with the BAGLE Python Package Bhadra, T. Dex Lu, J. R. Abrams, Natasha S. Scharf, Andrew Broadberry, Edward Lam, Casey Huston, Macy J. Solar and Stellar Astrophysics Earth and Planetary Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics Gravitational microlensing is a powerful tool that can be used to find and measure the mass of isolated and dark compact objects. In many microlensing events, the lens, the source, or both may be a binary system. In this work, we introduce binary source and lens models into the gravitational lensing formalism encoded in the Bayesian Analysis of Gravitational Lensing Events (BAGLE) Python software package. These new binary models in BAGLE account for Keplerian orbits. We also add binary models with fewer parameters that describe the binary orbital motion as acceleration, linear, or stationary motion of the secondary companion; these are useful when the orbit has a very low eccentricity or the orbital period is much longer than the microlensing timescale. The model parameterizations based on these binary lensing equations enable joint-fitting of photometric and astrometric datasets. These binary models will be used to fit microlensing event data from the Vera C. Rubin Observatory, the Nancy Grace Roman Telescope, and other surveys. |
| title | Modeling Binary Lenses and Sources with the BAGLE Python Package |
| topic | Solar and Stellar Astrophysics Earth and Planetary Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2512.03392 |